https://github.com/guptaachin/learn-llmchain
Getting started with LLM using HuggingFace
https://github.com/guptaachin/learn-llmchain
Last synced: 3 months ago
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Getting started with LLM using HuggingFace
- Host: GitHub
- URL: https://github.com/guptaachin/learn-llmchain
- Owner: guptaachin
- License: mit
- Created: 2024-04-13T18:59:37.000Z (about 1 year ago)
- Default Branch: main
- Last Pushed: 2024-04-13T23:20:24.000Z (about 1 year ago)
- Last Synced: 2025-01-14T06:46:07.848Z (4 months ago)
- Language: Python
- Homepage:
- Size: 14.6 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# Stable first steps towards LLMs
## Description
This repository contains the source code for getting started with LLMs. The project is developed in Python and leverages advanced language models to generate descriptive text based on user-defined topics and word counts.
## Features
- Generate descriptive text on any topic within a specified word count.
- Utilize pre-trained language models from the Hugging Face model hub.
- Accept command-line arguments for topic selection and word count customization.
- Easily customize prompts and language model configurations for specialized use cases.
## Getting Started
These instructions will get you a copy of the project up and running on your local machine for development and testing purposes.
### Prerequisites
- Python (version 3.12)
- Pipenv
### Installation
1. Clone the repository:
```bash
git clone https://github.com/guptaachin/learn-llmchain.git
```
2. Navigate to the project directory:
```bash
cd learn-llmchain
```
3. Run the `run.sh` script:
- On Linux:
```bash
./run.sh
```
- On Windows (using Git Bash or similar):
```bash
bash run.sh
```
4. Follow the on-screen instructions to install Pipenv if it's not already installed.
### Usage
1. After running the `run` script, activate the virtual environment:
```bash
pipenv shell
```
2. Follow the additional instructions provided after activating the virtual environment.
### Additional Instructions
- Create a Hugging Face API token. You can create one [here](https://huggingface.co/join).
- Create a `.env` file in the current directory. Add your Hugging Face API token to the `.env` file as `HUGGINGFACE_TOKEN=your_token_here`.
- Run your Python application using:
```bash
python main.py --topic life --length 5
```
## License
This project is licensed under the MIT License - see the [LICENSE.md](LICENSE.md) file for details.
## References
- [Langchain-docs](https://api.python.langchain.com/en/latest/langchain_api_reference.html)
- [Hugging Face](https://huggingface.co/)